In chemical processes, it would be much beneficial to develop a technique to precisely predict the standard chemical exergy values of different compounds. In this study, a multi-layer perceptron (MLP) network model is developed by using a set of 134 data points obtained from the literature. 114 and 24 Numbers of data points were allocated to training and testing steps, respectively. In addition, molecular weight, number of atoms, and sum of atomic polarizabilities properties were selected as input parameters to be the representative of the substances under consideration. The R-2 and AARE values were 0.9976 and 2.786, respectively, and the experimental and predicted exergy values showed a great overlap with each other. In fact, based on the results obtained in this paper, the proposed MLP model could be represented as a novel technique in order to calculate the standard chemical exergy values of different compounds.